Apparatus and method for converting preference color

ABSTRACT

An apparatus and method are provided for converting a preference color, in which the color space of a preference color selected by a user is divided into a plurality of sub-regions according to color distribution characteristics, and the colors of the respective regions of an input image corresponding to the user&#39;s preference color are converted into colors of proper sub-regions among the plurality of sub-regions. The apparatus for converting a preference color includes an image extraction unit which extracts at least one image region that includes a preference color from an input image, an image analysis unit which analyzes color distribution characteristics of the image region, a color-space extraction unit which extracts a divided space corresponding to the color distribution characteristics from divided spaces included in a color space of the preference color, and a color conversion unit which converts a color of the image region by using a color conversion model corresponding to the extracted divided space.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based on and claims priority from Korean PatentApplication No. 10-2005-0121836, filed on Dec. 12, 2005 in the KoreanIntellectual Property Office, the disclosure of which is incorporatedherein in its entirety by reference.

BACKGROUND OF THE INVENTION

1. Field of the invention

Apparatuses and methods consistent with the present invention relate toconverting a preference color and, more particularly, to converting apreference color by dividing the color space of a preference colorselected by a user into a plurality of sub-regions according to colordistribution characteristics, and converting the colors of therespective regions of an input image corresponding to the user'spreference color into colors of proper sub-regions among the pluralityof sub-regions.

2. Description of the Related Art

Digital imaging devices that reproduce colors, such as monitors,scanners, and printers, have diverse functions and high quality thatmeet various user requirements. Also, the digital imaging devices usedifferent color spaces or different color models depending on theirrespective fields of use. Examples of the color models include a devicedependent color model and a device independent color model. The devicedependent color model includes an RGB color model corresponding to anadditive color space model and a CMYK color model corresponding to asubtractive color space model. The device independent color modelincludes a CIE LAB model, a CIE XYZ model, and a CIE LUV model.

The CIE LAB model quantifies colors defined by the CommissionInternationale de l'Eclairage on color space coordinates, and expressesthe colors as numerical values of an L* (lightness), a* (red-green), andb* (yellow-blue) series. The CIE XYZ model represents RGB tristimulusvalues as XYZ, which is a set of other tristimulus values havingpositive signs. The CMYK color model is used in the field of printing,while the RGB color model is used in the field of computer monitordisplays, such as Internet graphics.

The digital imaging device may output colors of an input image as theyare, or convert specified colors among colors of an input image andoutput the converted colors of the input image. Accordingly, a user canview an image with the converted colors that are more natural.

General users' preference colors may include a skin color, a blue-skycolor, and a green grass color. A related color conversion algorithmperforms color conversion based on a single region that includes auser's preference color if the corresponding region is included in aninput image.

That is, if two regions including a skin color that is a user'spreference color exist in an image, the conventional color conversionalgorithm performs a uniform color conversion on colors of the twocorresponding regions.

As described above, the conventional algorithm can perform the uniformcolor conversion on the corresponding regions, but cannot perform colorconversion in consideration of the color distribution characteristics ofthe respective regions.

Accordingly, a method that can perform color conversion by regions of animage in consideration of the color distribution characteristics of therespective regions is required.

SUMMARY OF THE INVENTION

Exemplary embodiments of the present invention overcome the abovedisadvantages and other disadvantages not described above. Also, thepresent invention is not required to overcome the disadvantagesdescribed above, and an exemplary embodiment of the present inventionmay not overcome any of the problems described above.

The present invention provides an apparatus and method for converting apreference color, which divides the color space of a preference colorselected by a user into a plurality of sub-regions according to colordistribution characteristics, and converts the colors of the respectiveregions of an input image corresponding to the user's preference colorinto colors of proper sub-regions among the plurality of sub-regions.

According to an aspect of the present invention, there is provided anapparatus for converting a preference color, which includes an imageextraction unit which extracts at least one image region that includes auser's preference color from an input image, an image analysis unitwhich analyzes color distribution characteristics of the image region, acolor-space extraction unit which extracts a divided space correspondingto the color distribution characteristics from divided spaces includedin a color space of the preference color, and a color conversion unitwhich converts a color of the image region by using a color conversionmodel corresponding to the extracted divided space.

In another aspect of the present invention, there is provided a methodof converting a preference color, which includes extracting at least oneimage region that includes a user's preference color from an inputimage, analyzing color distribution characteristics of the image region,extracting a divided space corresponding to the color distributioncharacteristics from divided spaces included in a color space of thepreference color, and converting a color of the image region by using acolor conversion model corresponding to the extracted divided space.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects of the present invention will become moreapparent from the following detailed description of exemplaryembodiments taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a block diagram illustrating the construction of an apparatusfor converting a preference color according to an exemplary embodimentof the present invention;

FIG. 2 is a block diagram illustrating the construction of a color-spaceextraction unit according to an exemplary embodiment of the presentinvention;

FIG. 3 is a conceptual view illustrating extraction of image regionsaccording to an exemplary embodiment of the present invention;

FIG. 4 is a view illustrating a color space according to an exemplaryembodiment of the present invention;

FIG. 5 is a view illustrating a color distribution table according to anexemplary embodiment of the present invention;

FIG. 6 is a view illustrating conversion of colors in an image region inaccordance with a color conversion model according to an exemplaryembodiment of the present invention;

FIG. 7 is a view illustrating a color conversion table according to anexemplary embodiment of the present invention; and

FIG. 8 is a flowchart illustrating a process of converting a preferencecolor according to an exemplary embodiment of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS OF THE INVENTION

Hereinafter, exemplary embodiments of the present invention will bedescribed in detail with reference to the accompanying drawings. Theaspects and features of the present invention and methods for achievingthe aspects and features will be apparent by referring to the exemplaryembodiments to be described in detail with reference to the accompanyingdrawings. However, the present invention is not limited to the exemplaryembodiments disclosed hereinafter, but can be implemented in diverseforms. The matters defined in the description, such as the detailedconstruction and elements, are provided to assist those of ordinaryskill in the art in a comprehensive understanding of the invention, andthe present invention is only defined within the scope of the appendedclaims and their legal equivalents. In the entire description of thepresent invention, the same drawing reference numerals are used for thesame elements across various figures.

Exemplary embodiments of the present invention will be described hereinwith reference to the accompanying drawings illustrating block diagramsand flowcharts for explaining an apparatus and method for converting apreference color. Each block of the flowcharts, and combinations ofblocks in the flowcharts, can be implemented by computer programinstructions. These computer program instructions can be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions specified in the flowchart block or blocks.

These computer program instructions may also be stored in a computerusable or computer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer usable orcomputer-readable memory produce instruction means that implement thefunction specified in the flowchart block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus, in order to produce a computer implemented process such thatthe instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Also, each block of the flowchart illustrations may represent a module,segment, or portion of code, which comprises one or more executableinstructions for implementing the specified logical function(s). Itshould also be noted that in some alternative implementations, thefunctions noted in the blocks may occur out of order. For example, twoblocks shown in succession may be executed substantially concurrently,or in reverse order, depending upon the functionality involved.

FIG. 1 is a block diagram illustrating an apparatus for converting apreference color according to an exemplary embodiment of the presentinvention. Referring to FIG. 1, a color conversion apparatus 100includes an image receiving unit 110, an image extraction unit 120, animage analysis unit 130, a color-space extraction unit 140, a storageunit 150, a color conversion unit 160, and an image output unit 170.

The image receiving unit 110 receives an image. Here, the received imagemay be an analog image or a digital image, and the image receiving unit110 may convert a received analog image into a digital image.

If the color model of the received image is an RGB (Red, Green, Blue)color model, which is an additive color space model, the image receivingunit 110 can convert it into a CIE LAB color model, which is a uniformcolor space model, and particularly, can convert it into a CIE LCH(Lightness, Chroma, Hue) color model. Accordingly, the image extractionunit 120 can receive an image of the LCH color model from the imagereceiving unit 110.

Here, the LCH color model is a color model composed of lightness,chroma, and hue, and the respective constituent elements may beindicated as L*, C*, and h*.

The image extraction unit 120 extracts at least one image region thatincludes a user's preference color from the image transferred from theimage receiving unit 110.

Here, the preference color is a color sensitively reacted to orpreferred by a user, and includes a skin color, a sky-blue color, and agreen grass color. With supplement of the preference color only, theuser can feel that he/she views an image of a high picture quality.

In the present invention, however, the preference color is not limitedto the skin color, sky-blue color, and green grass color, and any othercolor may be set by a user as his/her preference color.

The image extraction unit 120 can separately extract image regions for aplurality of preference colors. In the case where two or more objectshaving the same preference color exist in an image, being apart fromeach other over a predetermined distance, the image extraction unit 120may separately extract the corresponding image regions. An inherentidentification number may be given to the extracted image region, anddifferent identification numbers may be given not only to image regionshaving different preference colors, but also to image regions having thesame preference color, depending on their arrangements.

The extracted image regions are transferred to the image analysis unit130, and the image analysis unit 130 analyzes the color distributioncharacteristics of the transferred image regions. The color distributioncharacteristics include averages and standard deviations of the colorspace of the pixels included in the image region. Here, a CIE LAB colorspace, CIE XYZ color space, or CIE LUV color space can be used as thecolor space.

In addition, the image analysis unit 130 converts the lightness of thewhole pixels included in an image into a preset reference size, and thenanalyzes the average and standard deviation of the transferred imageregion. This makes it possible to smoothly perform the extraction of thecolor space through the color-space extraction unit 140, which will beexplained later.

The color-space extraction unit 140 extracts a divided space thatcorrespond to the color distribution characteristics of the image regionamong divided spaces included in the color space of the preferencecolor.

As illustrated in FIG. 4, a color space 400 of a specified preferencecolor may be divided into a plurality of divided spaces, and therespective divided space 450 can be expressed in a color distributiontable 500 as shown in FIG. 5.

Once the color distribution characteristics of the image regions, i.e.,an average and standard deviation of the image region, are transferredfrom the image analysis unit 130, the color-space extraction unit 140confirms an overlapping region between the color space 400 formedaccording to the color distribution characteristics and the dividedspaces 450. At this time, by substituting values of colors of respectivepoints that form the external shape of the divided space 450 in thecolor distribution characteristics of the image region, the overlappingregion can be judged.

The color-space extraction unit 140 extracts a divided space having thelargest overlapping part among the divided spaces 450, and transfers theextracted divided space 450 to the color conversion unit 160.

A color distribution table 500 that the color-space extraction unit 140refers to in order to extract the divided space 450 may be stored in thestorage unit 150. This storage unit 150, which is a module that caninput/output information such as a hard disk, a flash memory, a compactflash card (CF card), a secure digital card (SD card), a smart mediacard (SM card), a multimedia card (MMC), and a memory stick, may beprovided inside the color conversion apparatus 100 or in a separateapparatus.

The color conversion unit 160 converts the colors of the respectiveimage regions extracted by the image extraction unit 120 by using acolor conversion model corresponding to the color space 400 extracted bythe color-space extraction unit 140. Here, the color space 400 may be adivided space 450 extracted by the color-space extraction unit 140.

For example, if the image region extracted by the image extraction unit120 refers to a skin color, the color-space extraction unit 140 extractsan optimum divided space 450 that most nearly corresponds to thecorresponding image region among the divided spaces 450 included in thecolor space 400 of the skin color, and the color conversion unitconverts the color of the corresponding image region in accordance withthe color conversion model corresponding to an optimum divided space.

The color conversion in the image region, which is performed by thecolor conversion unit 160, is applied to all pixels included in thetransferred image region, and the color conversion unit 160 converts thecolor of the pixels with the adjustment of the size of the colorconversion included in the color conversion model in proportion to thecolor of the pixels included in the image region.

A detailed explanation on the color conversion according to theconversion rate will be made later with reference to FIG. 6.

The image output unit 170 outputs the image region converted by thecolor conversion unit 160. The image output unit 170 may be a modulewith an image display means, such as a cathode ray tube (CRT), a liquidcrystal display (LCD), a light-emitting diode (LED), an organiclight-emitting diode (OLED), and a plasma display panel (PDP), todisplay the transferred image region; or a module provided with an imageprinting means, such as a printer, to print the transferred imageregion. The image output unit 170 may be provided inside the colorconversion apparatus 100 or in a separate apparatus.

FIG. 2 is a block diagram illustrating the construction of a color-spaceextraction unit according to an exemplary embodiment of the presentinvention.

In order to extract the divided space 450 corresponding to the colordistribution characteristics of the extracted image region, thecolor-space extraction unit 140 may include a color-space determinationunit 141 and a divided-space determination unit 142.

The color-space determination unit 141 determines an optimum color space400 that most nearly includes the color distribution characteristics ofthe extracted image region among the color spaces 400 determinedaccording to the preference color. Here, the color-space determinationunit 141 determines the color space 400 that most nearly overlaps thecolor distribution characteristics by substituting values of respectivepoints that form the external shape of the color space 400 in the colordistribution characteristics of the extracted image region. For this,the color-space determination unit 141 uses an average and standarddeviation of colors of pixels included in the image region. That is, thecolor-space determination unit 141 substitutes values of main points 405that form the color space 400 in the color distribution characteristics,and determines an optimum color space 400 using probability valuescalculated as a result of substitution.

The divided-space determination unit 142 determines an optimum dividedspace 450 that corresponds to the color distribution characteristicsamong a plurality of divided spaces 450 included in the optimum colorspace. Here, the divided-space determination unit 142 determines thedivided space 450 that most nearly overlaps the color distributioncharacteristics by substituting values of respective points that formthe external shapes of divided spaces 450 in the color distributioncharacteristics of the extracted image region. For this, thedivided-space determination unit 142 uses an average and standarddeviation of colors of pixels included in the image region. That is, thedivided-space determination unit 142 substitutes values of main points455 that form the divided space 450 in the color distributioncharacteristics, and determines an optimum divided space 450 usingprobability values calculated as a result of substitution.

FIG. 3 is a conceptual view illustrating extraction of image regionsaccording to an exemplary embodiment of the present invention. FIG. 3shows that image regions 310, 320, 330, 340, and 350 are extracted froman input image 200 according to preference colors by the imageextraction unit 120.

As described above, the image extraction unit 120 can separately extractimage regions for a plurality of preference colors. In the case wheretwo or more objects having the same preference color exist in an image200, and are apart from each other over a predetermined distance, theimage extraction unit 120 may separately extract the corresponding imageregions.

The image 200 of FIG. 3 includes the sky 210, clouds 220 a and 220 b,mountains 230 a and 230 b, a river 240, the ground 250, and human beings260 a and 260 b. Here, if it is assumed that the preference colors setby a user are a skin color, a sky-blue color, and a green grass color,the sky 210 including the sky-blue color occupies one region in theinput image, and the human beings 260 a and 260 b including the skincolor occupy two regions at a specified distance. Also, the mountains230 a and 230 b including the green grass color occupy two regions at aspecified distance (corresponding to the width of the river).

Accordingly, the image extraction unit 120 can extract one image region310 including the sky-blue color, two image regions 320 and 330including the green grass color, and two image regions 340 and 350including the skin color. That is, if image regions including the samepreference color, such as the mountains 230 a and 230 b or the humanbeings 260 a and 260 b, are apart from each other over a predetermineddistance, the image extraction unit 120 extracts the image regions 320,330, 340, and 350 separately.

The colors of the extracted image regions are converted by the colorconversion unit 160 according to the color conversion model of theextracted divided spaces 450, and thus the color conversion apparatus100 can perform a closer color conversion on the input image 200.

FIG. 4 is a view illustrating a color space according to an exemplaryembodiment of the present invention. As shown in FIG. 4, the color space400 is composed of a plurality of divided spaces 450.

Respective color spaces 400 may exist according to a user's preferencecolors. If the color space 400 according to the preference color iscomposed of one color space, it is impossible to perform a closer colorconversion on the input image, and thus the color conversion apparatus100 according to the present invention performs the color conversionusing the color space 400 divided into a plurality of divided spaces450.

That is, the color-space extraction unit 140 extracts the divided space450 that most nearly overlaps the corresponding image region in thecolor space 400 corresponding to the preference color of the input imageregion, and the color conversion unit 160 converts the color of thecorresponding image region using the color conversion model thatcorresponds to the divided space 450 extracted by the color-spaceextraction unit 140.

The color space 400 of FIG. 4 is a color space drawn according to theCIE LAB color space, and the color space 400 may be in accord with theCIE XYZ color space or the CIE LUV color space, depending on the user'sselection.

In addition, when color spaces 400 according to the CIE LAB color space,CIE XYZ color space, and CIE LUV color space have been defined, thecolor-space extraction unit 140 may extract the most overlapping dividedspace 450 by substituting the input image regions in the color spaces400 included in all the defined color spaces.

For example, when the first image region and the second image region areinputted, color conversion may be performed on the first image region inaccordance with the color conversion model that corresponds to thedivided space 450 according to the CIE LAB color space, and colorconversion may be performed on the second image region in accordancewith the color conversion model that corresponds to the divided space450 according to the CIE XYZ color space.

Although FIG. 4 shows a divided space 450 in the form of a dodecahedronof which the external shape is formed by 10 corner points, the dividedspace 450 may also be in a hexahedron form, a cylinder form, or anyother 2-dimensional or 3-dimensional geometrical form.

The respective divided spaces may be arranged to overlap one another,and the number and color range of the divided spaces 450 may be set by auser.

The color-space extraction unit 140 extracts an optimum divided space450 by substituting the divided space 450 in the color distributioncharacteristics of the image region transferred from the image analysisunit 130. In this case, the optimum divided space 450 can be extractedby substituting positions of main points 455 that form the divided space450 in the color distribution characteristics. In other words, colorinformation corresponding to the main points 455, e.g., values of CIELAB, CIE XYZ, or CIE LUV, is substituted in the color distributioncharacteristics of the image region. Here, the main points 455 may becorner points that form the divided space 450 or separate points set bythe user.

For this, color information of the main points 455 that form the dividedspace 450 may be stored in the form of a table by the storage unit 150.

FIG. 5 is a view illustrating a color distribution table according to anexemplary embodiment of the present invention. The color distributiontable 500 may be separately constructed according to the preferencecolors, and may include color information 550 of the main points 455that form the external shape of the divided space 450. For this, thecolor distribution table 500 includes a main-point field 510 and dividedspace fields 520, 530, and 540.

The color distribution table 500 is a table that includes the colorinformation 550 defining the color space 400, and includes the colorinformation 550 defining the shape of the divided space 450 included inthe color space 400. In this case, the color information 550 may becolor information on the main points 455 of the geometrical shape thatforms the divided space 450. If the geometrical shape has corner points,such as a hexahedron or a dodecahedron, the corner points of thegeometrical shape may correspond to the main points 455.

Here, the color information 550 may be CIE LAB, CIE XYZ, CIE LUV, andL*C*h values, or may be RGB values, depending on whether the colorconversion apparatus 100 has been implemented.

The color distribution characteristics of the image region include theaverage and standard deviation, and the color-space extraction unit 140substitutes the color information 550 of the main points 455 thatcorrespond to the divided spaces 450 included in the color distributiontable 500 in the color distribution characteristics of the image region,and calculates its probability values. Then, the color-space extractionunit 140 determines the divided space 450, in which the greatestprobability value has been calculated, as an optimum divided space 450.

FIG. 6 is a view illustrating conversion of colors in an image region inaccordance with a color conversion model according to an exemplaryembodiment of the present invention. As shown in FIG. 6, colors ofpixels included in the image region are converted in proportion to thedistance between an initial point and an end point that is determinedaccording to the color conversion model.

The color conversion model, which is to convert colors corresponding tothe pixels of the image region included in the corresponding dividedspace 450, converts the colors corresponding to the pixels of the imageregion in proportion to the distance between the color information ofthe initial point and the color information of the end point.

FIG. 6 shows the conversion of the color of a specified pixel in theimage region that is included in the divided space 450 extracted by thecolor-space extraction unit 140. Hereinafter, it is assumed that theinitial point of the color conversion model is C₀(610 a), the end pointis C₁(610 b), a point indicating a color of a specified pixel of aninput image region is C_(i)(620 a), and a point indicating a color of aconverted pixel is C_(ip)(620 b).

The color conversion unit 160 first forms a straight line L₀(630 a) thatconnects the initial point C₀(610 a) with the point C_(i)(620 a), andextracts a point P (650) at which the straight line L₀(630 a) intersectsthe external shape of the divided space 450. Then, the color conversionunit 160 forms a straight line L₁(630 b) that connects the point P (650)with the end point C₁(610 b), and forms a straight line L₀₁(640 a) thatconnects the initial point C₀(610 a) with the end point C₁(610 b).

Then, the color conversion unit 160 forms a straight line L_(ip)(640 b)that connects the point C_(i)(620 a) with a straight line L₁(630 b) atthe same angle as that between the lines L₀₁(640 a) and L₀(630 a), andextracts a point C_(ip)(620 b) at which the straight line L₁(630 b)intersects the straight line L_(ip)(640 b).

The point C_(ip)(620 b) is a point that indicates a converted color withrespect to the color of the pixel of the input image region, andconsequently, it is determined in proportion to the distance between thepoints C₀(610 a) and C₁(610 b).

Here, the distance 640 a between the points C₀(610 a) and C₁(610 b)calculated to determine the point C_(ip)(620 b), the distance 630 abetween the points P (650) and C₀(610 a), the distance 630 b between thepoints P (650) and C₁(610 b), and the distance 640 b between the pointsC_(i)(620 a) and C_(ip)(620 b) can be calculated by CIE delta E 2000.

The initial point C₀(610 a) and the end point C₁(610 b) are setdifferently by different color conversion models, and the user can setthe initial point 610 a and the end point 610 b of the color conversionform intended by the user by color conversion models. The initial point610 a and the end point 610 b set by color conversion models may bestored in the storage unit 150 in the form of a table, as shown in FIG.7.

FIG. 7 is a view illustrating a color conversion table according to anexemplary embodiment of the present invention. The color conversiontable 700 includes an initial point 710 and an end point 720 accordingto the color space defined by CIE LAB color model by color conversionmodels 750 a, 750 b, 750 c, 750 d, and 750 e.

In the CIE LAB color model, L* denotes lightness, a* denotes acombination of red and green, and b* denotes a combination of yellow andblue. A user can generate a desired color conversion model by settingL*, a*, and b* values of the initial point 710 and the end point 720according to the color conversion model. That is, the user can generatethe color conversion model by modifying lightness or specified colors.

In FIG. 7, the value of L* of the end point of the firstcolor-conversion model 750 a is somewhat less than the value of L* ofthe initial point, and the values of a* and b* of the end point aresimilar to the values of a* and b* of the initial point. This decreaseof L* causes a decrease of lightness. Also, the values of L* and a* ofthe end point of the second conversion model 750 b are somewhat greaterthan the value of L* and a*, respectively, of the initial point, and thevalue of b* of the end point is somewhat less than the value of b* ofthe initial point. This increase of L* and a*causes a decrease ofyellow.

As described above, the user can set the lightness and the colors of theinitial point and the end point when generating the color conversionmodel for converting the colors of the image region. In order toincrease lightness and decrease red, the user can set the values of theinitial point and the end point according to the third color-conversionmodel 750 c, while in order to increase lightness and decrease chroma,the user can set the values of the initial point and the end pointaccording to the fourth color-conversion model 750 d. Also, in order toincrease lightness, the user can set the values of the initial point andthe end point according to the fifth color-conversion model 750 e.

FIG. 7 illustrates the use of CIE LAB as the color model of the initialpoint and the end point. However, a CIE XYZ or CIE LUV color model canalso be used instead.

FIG. 8 is a flowchart illustrating a process of converting a preferencecolor according to an exemplary embodiment of the present invention.

In order to convert the preference colors set by the user and includedin an image, the image receiving unit 110 of the color conversionapparatus 100 receives the image (S810). The color model of the receivedimage may be an RGB color model or CMYK color model, and the imagereceiving unit 110 can convert the received image into a CIE LAB colormodel or a CIE LCH color model.

Accordingly, the image of the LCH color model is transferred to theimage extraction unit 120, and the image extraction unit 120 extracts atleast one image region included in the user's preference colors in theimage transferred from the image receiving unit 110 (S820). Thepreference colors may include a skin color, a sky-blue color, and agreen grass color, or other colors may be set as the user's preferencecolors.

The image extraction unit 120 can perform the extraction of an imageregion according to the preference colors, and the extraction of animage region according to the arrangement of the image region. That is,when a plurality of regions having the same preference color exists, theimage extraction unit 120 extracts one image region, considering theplurality of regions as the same region, if the plurality of regions areclosely arranged, while the image extraction unit 120 extracts aplurality of regions separately if the plurality of regions are arrangedto be apart from each other over a predetermined distance.

The extracted image regions are transferred to the image analysis unit130, and the image analysis unit 130 analyzes the color distributioncharacteristics of the transferred image regions (S830). The colordistribution characteristics include averages and standard deviations ofthe color spaces of pixels included in the image regions. Here, thecolor space may be a CIE LAB color space, a CIE XYZ color space, or aCIE LUV color space.

In order to make the color-space extraction unit 140 smoothly extractthe color space 400, the image analysis unit 130 may convert thelightness of the whole pixels included in the image into a presetreference size, and then analyze the average and standard deviation ofthe color space with respect to the image regions.

The image analysis unit 130 transfers the analyzed color distributioncharacteristics to the color-space extraction unit 140, and transfersthe image received from the image receiving unit 110 to the colorconversion unit 160.

The color-space extraction unit 140 extracts the divided space 450 thatcorresponds to the color distribution characteristics of the imageregion among the divided spaces 450 included in the color space 400 ofthe preference color (S840).

For this, the color-space extraction unit 140 determines the optimumcolor space 400 that most nearly includes the color distributioncharacteristics of the image region in the color space 400, and thendetermines the optimum divided space 450 that corresponds to the colordistribution characteristics among the plurality of divided spaces 450included in the determined optimum color space 400.

In order to determine the optimum color space 400 and the optimumdivided space 450, the color-space extraction unit 140 uses the averageand the standard deviation of the colors of the pixels included in theimage region. That is, the color-space extraction unit 140 substitutesthe values of the main points 455 that form the divided space 450 in thecolor distribution characteristics, and extracts the optimum dividedspace 450 by using the probability value calculated as a result ofsubstitution.

The color conversion model that corresponds to the divided space 450extracted by the color-space extraction unit 140 is transferred to thecolor conversion unit 160, and the color conversion unit 160 convertsthe color of the image region transferred from the image analysis unit130 by using the color conversion model transferred from the color-spaceextraction unit 140 (S850). That is, the color conversion unit 160converts the color of the pixels by proportionally adjusting the size ofthe color conversion included in the color conversion model inaccordance with the color of the pixels included in the image region.

The color-converted image regions are combined with other image regionsnot extracted by the image extraction unit 120 to be provided as aconverted image, and the image output unit 170 outputs thecolor-converted image (S860).

As described above, the apparatus and method for converting a preferencecolor according to exemplary embodiments of the present invention hasone or more of the following effects.

A color space of a preference color selected by a user is divided into aplurality of sub-regions according to color distributioncharacteristics, and colors of the respective regions of an input imagecorresponding to the user's preference color are converted into colorsof proper sub-regions among the plurality of sub-regions. Accordingly,the respective regions included in the preference color can be expressedin consideration of the colors of neighboring images.

Exemplary embodiments of the present invention have been described forillustrative purposes, and those skilled in the art will appreciate thatvarious modifications, additions and substitutions are possible withoutdeparting from the scope and spirit of the invention as disclosed in theaccompanying claims. Therefore, the scope of the present inventionshould be defined by the appended claims and their legal equivalents.

1. An apparatus for converting a preference color, the apparatuscomprising: an image extraction unit which extracts a plurality of imageregions that include a preference color from an input image; an imageanalysis unit which analyzes color distribution characteristics of eachof the plurality of image regions; a color-space extraction unit whichextracts a divided space corresponding to the color distributioncharacteristics of each of the plurality of image regions from aplurality of divided spaces included in a color space of the preferencecolor; and a color conversion unit which converts a color of each of theplurality of image regions by using a color conversion modelcorresponding to the divided space which is extracted.
 2. The apparatusof claim 1, wherein the preference color comprises at least one of askin color, a blue color, and a green color.
 3. The apparatus of claim1, wherein the preference color is selected by a user.
 4. The apparatusof claim 1, wherein the color distribution characteristics comprise anaverage and a standard deviation of colors of pixels included in each ofthe plurality of image regions.
 5. The apparatus of claim 4, wherein theimage analysis unit analyzes the average and the standard deviationafter lightness of whole pixels included in the image is converted intoa reference size.
 6. The apparatus of claim 1, wherein the color spaceis one of a CIE LAB color space, a CIE XYZ color space, and a CIE LUVcolor space.
 7. The apparatus of claim 1, wherein the color-spaceextraction unit comprises: a color-space determination unit whichdetermines an optimum color space that most nearly includes the colordistribution characteristics among color spaces; and a divided-spacedetermination unit which determines an optimum divided space that mostnearly includes the color distribution characteristics among a pluralityof divided spaces included in the optimum color space.
 8. The apparatusof claim 7, wherein the color-space determination unit determines theoptimum color space using an average and a standard deviation of colorsof pixels included in each of the plurality of image regions.
 9. Theapparatus of claim 7, wherein the divided-space determination unitdetermines the optimum divided space using an average and standarddeviation of colors of pixels included in each of the plurality of imageregions.
 10. The apparatus of claim 1, wherein the color conversion unitconverts colors of pixels by adjusting a size of color conversionincluded in the color conversion model in proportion to the colors ofthe pixels included in each of the plurality of image regions.
 11. Amethod of converting a preference color, the method comprising:extracting a plurality of image regions that include a preference colorfrom an input image; analyzing color distribution characteristics ofeach of the plurality of image regions; extracting a divided spacecorresponding to the color distribution characteristics of each theplurality of image regions from divided spaces included in a color spaceof the preference color; and converting a color of each of the pluralityof image regions by using a color conversion model corresponding to thedivided space which is extracted.
 12. The method of claim 11, whereinthe preference color comprises at least one of a skin color, a bluecolor, and a green color.
 13. The method of claim 11, wherein thepreference color is selected by a user.
 14. The method of claim 11,wherein the color distribution characteristics comprise an average and astandard deviation of colors of pixels included in each of the pluralityof image regions.
 15. The method of claim 14, wherein the analyzing thecolor distribution characteristics of the image region comprisesanalyzing the average and the standard deviation after lightness ofwhole pixels included in the image is converted into a preset referencesize.
 16. The method of claim 11, wherein the color space is one of aCIE LAB color space, a CIE XYZ color space, and a CIE LUV color space.17. The method of claim 11, wherein the extracting the divided spacecomprises: determining an optimum color space that most nearly includesthe color distribution characteristics among color spaces; anddetermining an optimum divided space that most nearly includes the colordistribution characteristics among a plurality of divided spacesincluded in the optimum color space.
 18. The method of claim 17, whereinthe determining the optimum color space comprises determining theoptimum color space using an average and a standard deviation of colorsof pixels included in each of the plurality of image regions.
 19. Themethod of claim 17, wherein the determining the optimum divided spacecomprises determining the optimum divided space using an average and astandard deviation of colors of pixels included in each of the pluralityof image regions.
 20. The method of claim 11, wherein the converting thecolor of the image region comprises converting colors of pixels byadjusting a size of color conversion included in the color conversionmodel in proportion to the colors of the pixels included in each of theplurality of image regions.